Next Article in Journal
Improving Prediction Intervals Using Measured Solar Power with a Multi-Objective Approach
Previous Article in Journal
Solid-State Transformers in Locomotives Fed through AC Lines: A Review and Future Developments
Open AccessArticle

Fault-Tolerant Neuro Adaptive Constrained Control of Wind Turbines for Power Regulation with Uncertain Wind Speed Variation

1
Faculty of Science and Engineering, School of Civil and Mechanical Engineering, Curtin University, Perth 6102, Australia
2
Center for Research in Mechatronics, Institute of Mechanics, Materials, and Civil Engineering, Université Catholique de Louvain, 1348 Louvain-la-Neuve, Belgium
3
Department of Engineering, University of Ferrara, 44100 Ferrara, Italy
*
Author to whom correspondence should be addressed.
Energies 2019, 12(24), 4712; https://doi.org/10.3390/en12244712
Received: 20 October 2019 / Revised: 25 November 2019 / Accepted: 9 December 2019 / Published: 10 December 2019
This paper presents a novel adaptive fault-tolerant neural-based control design for wind turbines with an unknown dynamic and unknown wind speed. By utilizing the barrier Lyapunov function in the analysis of the Lyapunov direct method, the constrained behavior of the system is provided in which the rotor speed, its variation, and generated power remain in the desired bounds. In addition, input saturation is also considered in terms of smooth pitch actuator bounding. Furthermore, by utilizing a Nussbaum-type function in designing the control algorithm, the unpredictable wind speed variation is captured without requiring accurate wind speed measurement, observation, or estimation. Moreover, with the proposed adaptive analytic algorithms, together with the use of radial basis function neural networks, a robust, adaptive, and fault-tolerant control scheme is developed without the need for precise information about the wind turbine model nor the pitch actuator faults. Additionally, the computational cost of the resultant control law is reduced by utilizing a dynamic surface control technique. The effectiveness of the developed design is verified using theoretical analysis tools and illustrated by numerical simulations on a high-fidelity wind turbine benchmark model with different fault scenarios. Comparison of the achieved results to the ones that can be obtained via an available industrial controller shows the advantages of the proposed scheme. View Full-Text
Keywords: adaptive constrained control; barrier Lyapunov function; fault-tolerant control; Nussbaum-type function; pitch actuator; power regulation; robustness evaluation adaptive constrained control; barrier Lyapunov function; fault-tolerant control; Nussbaum-type function; pitch actuator; power regulation; robustness evaluation
Show Figures

Figure 1

MDPI and ACS Style

Habibi, H.; Rahimi Nohooji, H.; Howard, I.; Simani, S. Fault-Tolerant Neuro Adaptive Constrained Control of Wind Turbines for Power Regulation with Uncertain Wind Speed Variation. Energies 2019, 12, 4712.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop